Chladni

Nodal regularity, zero-crossing clustering, multi-scale modal complexity
dynamicalencoding-invariantdim nodal7 metrics

What It Measures

Two complementary views of the 1D signal — the plate eigenmode decomposition of a 2D reshape, and the nodal-point process formed by the signal's own zero-crossings.

The plate branch reshapes the signal into a 2D field and projects it onto the eigenmodes of a simply-supported rectangular Kirchhoff–Love plate (∇⁴w = λw with w = ∇²w = 0 on the boundary). The eigenmodes are φ_{mn} = sin(mπx/L)·sin(nπy/L) with eigenvalues λ_{mn} ∝ (m² + n²)² — literal Chladni-plate physics, where each φ_{mn}'s zero set is the nodal pattern along which sand collects. The biharmonic operator (the squared bracket) is what makes this a plate and not a membrane. The nodal branch is a random-matrix / multiscale analysis of the 1D signal's zero-crossings, treated as a vibrating-medium nodal process — Poisson predicts ⟨r⟩ ≈ 0.386 for uncorrelated gaps, GOE predicts ⟨r⟩ ≈ 0.536 for level-repelling spectra.

Metrics

nodal_gap_ratio

Mean consecutive spacing ratio r = min(sₙ, sₙ₊₁) / max(sₙ, sₙ₊₁) of zero-crossing intervals. Borrowed directly from random matrix theory: Poisson (uncorrelated crossings) gives ⟨r⟩ ≈ 0.386, GOE / Wigner (level-repelling, as in many-body quantum systems) gives ⟨r⟩ ≈ 0.536, and perfectly regular nodes give r = 1. Periodic waveforms saturate at 1.0 (Sine Wave, Square Wave, Van der Pol, every logistic periodic window), chaos sits near GOE (Logistic Edge-of-Chaos at 1.0 reflects near-regularity of the window), and noisy/clustered signals sit well below. The most discriminating metric in the geometry (F=8.61).

nodal_clustering

log(1 + Fano factor) of zero-crossing intervals; Fano = variance / mean, so Poisson gives F=1 and bursty crossings drive it upward. Devil's Staircase (8.96), fBm Persistent (8.41), ETH/BTC Ratio (8.18), and Perlin Noise (7.89) all have heavy zero-crossing burstiness — long quiet stretches punctuated by rapid flips. Correlates strongly with Möbius-S³:phi_return_cv (+0.817), flagging the same clustering signature from a different angle.

modal_nodal_cascade

Power-law exponent of zero-crossing count versus bandpass center frequency across six octave bands. Measures how pattern complexity grows with the "driving frequency" — the 1D analogue of how Chladni figures become more intricate at higher resonant modes. Weak discriminator (F=1.03, rank low) but picks out sources where the bandpassed structure genuinely scales across octaves versus signals whose spectra are concentrated in a narrow band.

domain_ks_exponential

Kolmogorov-Smirnov distance of positive/negative domain lengths from an exponential distribution. For Poisson crossings, domain lengths are exponential; structured signals deviate. Devil's Staircase (0.89), Temperature Drift (0.79), Rudin-Shapiro (0.73), LIGO Hanford/Livingston (0.72/0.67) all have strongly non-exponential domain distributions — clumped or bimodal — consistent with regime-switching or structured modulation. Discovered by ShinkaEvolve (chladni v1, direction #6).

plate_low_mode_fraction

Fraction of plate modal energy in the low-eigenvalue (λ ≤ median) half of the spectrum. Smooth fields sit in low-order modes (high score); high-frequency or scale-localized fields push energy into the upper half. Takagi Function (0.996), fBm Persistent (0.996), Riemann-Hardy-Littlewood (0.996), Minkowski ?(x) (0.994), and ETH/BTC Ratio (0.994) score highest — all signals whose reshaped 2D fields are dominated by smooth low-order plate modes. Logistic Period-2, Period-3, Period-5, and constants collapse to 0. The literal biharmonic-plate decomposition; sister metric plate_modal_entropy is class-only because it duplicates Spectral Analysis:spectral_entropy at r=0.93 (the plate eigenbasis IS the 2D DST).

temporal_burstiness

Gini coefficient of the octave-band envelope binned over time. Measures time-frequency localization / intermittency: high when bandpass energy is concentrated in a few time bins, near zero when it's spread evenly. Forest Fire (0.65), Speech "Five" (0.57), Rössler Hyperchaos (0.53), Lotka-Volterra (0.53), and Quantum Walk (0.52) score highest. Temperature Drift, Respiration Waveform, both LIGO channels, and Pressure all sit at 0 (stationary bandpass envelopes). Surfaced by PCA-driven embedding discovery and retained for empirical discrimination of intermittent vs. stationary signals.

captured_power_fraction

Fraction of signal variance falling inside the six octave bandpass bands. Distinguishes signals whose energy lives in the octave grid (most physical signals → 1.0) from signals whose energy is concentrated outside it. The four Torus Quasiperiodic sources and ARMA(2,1) all hit 1.0. Primes, Partition Function, Minkowski ?(x), and constants sit at 0 — these monotone or trivial sources put no power in the bandpass grid. Orthogonal to temporal_burstiness (which asks where in time the captured power lives) and to the plate metrics (which work on the 2D reshape).

Atlas Rankings

captured_power_fraction
SourceDomainValue
ARMA(2,1)noise1.0000
MFPT Normalbearing1.0000
Mackey-Glassmedical1.0000
···
Sine Wavewaveform0.0001
Takagi Functionexotic0.0006
Temperature Driftclimate0.0012
domain_ks_exponential
SourceDomainValue
Temperature Driftclimate0.7813
Respiration Waveformmedical0.7558
Rudin-Shapironumber_theory0.7272
···
OTOC Growthquantum0.0000
Random Telegraphexotic0.0465
Random Stepsexotic0.0559
modal_nodal_cascade
SourceDomainValue
Quantum Walkquantum2.1487
Sine Map (Feigenbaum)chaos2.1481
Logistic r=3.5 (Period-4)chaos2.0377
···
Damped Pendulummotion-0.6527
Duffing Oscillatorchaos-0.5758
2-Torus Quasiperiodicchaos-0.4942
nodal_clustering
SourceDomainValue
Spectral Form Factorquantum8.7156
Devil's Staircaseexotic8.2619
ETH/BTC Ratiofinancial8.1796
···
Sine Map (Feigenbaum)chaos0.0000
Logistic r=3.2 (Period-2)chaos0.0000
Logistic r=3.5 (Period-4)chaos0.0000
nodal_gap_ratio
SourceDomainValue
Logistic Edge-of-Chaoschaos1.0000
Logistic r=3.5 (Period-4)chaos1.0000
Logistic r=3.2 (Period-2)chaos1.0000
···
OTOC Growthquantum0.0000
Mian-Chowlanumber_theory0.0337
Spectral Form Factorquantum0.0719
plate_low_mode_fraction
SourceDomainValue
Riemann-Hardy-Littlewoodexotic0.9956
fBm (Persistent)noise0.9955
Takagi Functionexotic0.9950
···
Logistic r=3.2 (Period-2)chaos0.0000
Logistic r=3.83 (Period-3 Window)chaos0.0012
Logistic r=3.74 (Period-5 Window)chaos0.0026
temporal_burstiness
SourceDomainValue
Aubry-André Criticalquantum0.7671
Devil's Staircaseexotic0.7470
Forest Fireexotic0.6537
···
fBm (Antipersistent)noise0.0000
Brownian Walknoise0.0000
Regime Switchingnoise0.0000

When It Lights Up

Chladni asks two parallel questions: how does the signal decompose onto plate eigenmodes (the literal physics), and what are the statistics of its zero-crossings (the nodal process)? The plate branch (plate_low_mode_fraction, captured_power_fraction) sorts signals by smoothness and by whether their energy fits the octave grid. The nodal branch (nodal_gap_ratio, nodal_clustering, modal_nodal_cascade, domain_ks_exponential) sorts the atlas cleanly by dynamical class: periodic waveforms have regular spacings (nodal_gap_ratio → 1), chaotic attractors have GOE-like level repulsion, and heavy-tailed clustered processes (financial ratios, 1/f noise, seismic data) show elevated clustering with non-exponential domain lengths. temporal_burstiness adds a time-frequency intermittency channel that complements both branches. Not a chaos detector per se — a gap-statistics + plate-modal detector that happens to place chaotic systems in a different part of the plane than periodic or stochastic ones.

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